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The Temporal Neurogenesis Patterning of Spinal p3–V3 Interneurons into Divergent Subpopulation Assemblies

2019· article· en· W2994700376 on OpenAlexafffund
Dylan Deska‐Gauthier, Joanna Borowska-Fielding, Christopher T. Jones, Ying Zhang

Bibliographic record

VenueJournal of Neuroscience · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNeurogenesisNeuroscienceBiologyInterneuronEmbryonic stem cellSpinal cordProgenitor cellAnatomyStem cellInhibitory postsynaptic potentialCell biologyGeneticsGene

Abstract

fetched live from OpenAlex

Neuronal diversity provides the spinal cord with the functional flexibility required to perform complex motor tasks. Spinal neurons arise during early embryonic development with the establishment of spatially and molecularly discrete progenitor domains that give rise to distinct, but highly heterogeneous, postmitotic interneuron (IN) populations. Our previous studies have shown that Sim1-expressing V3 INs, originating from the p3 progenitor domain, are anatomically and physiologically divergent. However, the developmental logic guiding V3 subpopulation diversity remains elusive. In specific cases of other IN classes, neurogenesis timing can play a role in determining the ultimate fates and unique characteristics of distinctive subpopulations. To examine whether neurogenesis timing contributes to V3 diversity, we systematically investigated the temporal neurogenesis profiles of V3 INs in the mouse spinal cord. Our work uncovered that V3 INs were organized into either early-born [embryonic day 9.5 (E9.5) to E10.5] or late-born (E11.5–E12.5) neurogenic waves. Early-born V3 INs displayed both ascending and descending commissural projections and clustered into subgroups across dorsoventral spinal laminae. In contrast, late-born V3 INs became fate-restricted to ventral laminae and displayed mostly descending and local commissural projections and uniform membrane properties. Furthermore, we found that the postmitotic transcription factor, Sim1, although expressed in all V3 INs, exclusively regulated the dorsal clustering and electrophysiological diversification of early-born, but not late-born, V3 INs, which indicates that neurogenesis timing may enable newborn V3 INs to interact with different postmitotic differentiation pathways. Thus, our work demonstrates neurogenesis timing as a developmental mechanism underlying the postmitotic differentiation of V3 INs into distinct subpopulation assemblies. SIGNIFICANCE STATEMENTInterneuron (IN) diversity empowers the spinal cord with the computation flexibility required to perform appropriate sensorimotor control. As such, uncovering the developmental logic guiding spinal IN diversity is fundamental to understanding the development of movement. In our current work, through a focus on the cardinal spinal V3 IN population, we investigated the role of neurogenesis timing on IN diversity. We uncovered that V3 INs are organized into early-born [embryonic day 9.5 (E9.5) to E10.5] or late-born (E11.5–E12.5) neurogenic waves, where late-born V3 INs display increasingly restricted subpopulation fates. Next, to better understand the consequences of V3 neurogenesis timing, we investigated the time-dependent functions of the Sim1 transcription factor, which is expressed in postmitotic V3 INs. Interestingly, Sim1 exclusively regulated the diversification of early-born, but not late-born, V3 INs. Thus, our current work indicates neurogenesis timing can modulate the functions of early postmitotic transcription factors and, thus, subpopulation fate specifications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.046
GPT teacher head0.293
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations36
Published2019
Admission routes2
Has abstractyes

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